Optimize by trying out predefined configurations. More...

#include <shark/Algorithms/DirectSearch/GridSearch.h>

Inheritance diagram for shark::PointSearch:

Public Member Functions
	PointSearch ()
	Constructor.

std::string	name () const
	From INameable: return the class name.

void	configure (const std::vector< RealVector > &points)

void	configure (size_t parameters, size_t samples, double min, double max)
	samples random points in the range [min,max]^parameters

virtual void	read (InArchive &archive)
	Read the component from the supplied archive.

virtual void	write (OutArchive &archive) const
	Write the component to the supplied archive.

void	init (ObjectiveFunctionType const &objectiveFunction, SearchPointType const &startingPoint)
	If the class wasn't configured before, this method samples random uniform distributed points in [-1,1]^n.

void	step (ObjectiveFunctionType const &objectiveFunction)

Public Member Functions inherited from shark::AbstractSingleObjectiveOptimizer< RealVector >
std::size_t	numInitPoints () const
	By default most single objective optimizers only require a single point.

virtual void	init (ObjectiveFunctionType const &function, std::vector< SearchPointType > const &initPoints)
	Initialize the optimizer for the supplied objective function using a set of initialisation points.

virtual const SolutionType &	solution () const
	returns the current solution of the optimizer

Public Member Functions inherited from shark::AbstractOptimizer< PointType, ResultT, SolutionTypeT >
const Features &	features () const

virtual void	updateFeatures ()

bool	requiresValue () const

bool	requiresFirstDerivative () const

bool	requiresSecondDerivative () const

bool	canSolveConstrained () const

bool	requiresClosestFeasible () const

virtual	~AbstractOptimizer ()

virtual void	init (ObjectiveFunctionType const &function)
	Initialize the optimizer for the supplied objective function.

virtual void	init (ObjectiveFunctionType const &function, std::vector< SearchPointType > const &initPoints)=0
	Initialize the optimizer for the supplied objective function using a set of initialisation points.

virtual void	step (ObjectiveFunctionType const &function)=0
	Carry out one step of the optimizer for the supplied objective function.

Public Member Functions inherited from shark::INameable
virtual	~INameable ()

Public Member Functions inherited from shark::ISerializable
virtual	~ISerializable ()
	Virtual d'tor.

void	load (InArchive &archive, unsigned int version)
	Versioned loading of components, calls read(...).

void	save (OutArchive &archive, unsigned int version) const
	Versioned storing of components, calls write(...).

	BOOST_SERIALIZATION_SPLIT_MEMBER ()

Protected Attributes
std::vector< RealVector >	m_points
	The array holds one parameter configuration in every column.

bool	m_configured
	verbosity level

Protected Attributes inherited from shark::AbstractSingleObjectiveOptimizer< RealVector >
SolutionType	m_best
	Current solution of the optimizer.

Protected Attributes inherited from shark::AbstractOptimizer< PointType, ResultT, SolutionTypeT >
Features	m_features

Additional Inherited Members
Public Types inherited from shark::AbstractSingleObjectiveOptimizer< RealVector >
typedef base_type::SearchPointType	SearchPointType

typedef base_type::SolutionType	SolutionType

typedef base_type::ResultType	ResultType

typedef base_type::ObjectiveFunctionType	ObjectiveFunctionType

Public Types inherited from shark::AbstractOptimizer< PointType, ResultT, SolutionTypeT >
enum	Feature { REQUIRES_VALUE = 1 , REQUIRES_FIRST_DERIVATIVE = 2 , REQUIRES_SECOND_DERIVATIVE = 4 , CAN_SOLVE_CONSTRAINED = 8 , REQUIRES_CLOSEST_FEASIBLE = 16 }
	Models features that the optimizer requires from the objective function. More...

typedef PointType	SearchPointType

typedef ResultT	ResultType

typedef SolutionTypeT	SolutionType

typedef AbstractObjectiveFunction< PointType, ResultType >	ObjectiveFunctionType

typedef TypedFlags< Feature >	Features

typedef TypedFeatureNotAvailableException< Feature >	FeatureNotAvailableException

Protected Member Functions inherited from shark::AbstractOptimizer< PointType, ResultT, SolutionTypeT >
void	checkFeatures (ObjectiveFunctionType const &objectiveFunction)
	Convenience function that checks whether the features of the supplied objective function match with the required features of the optimizer.

Detailed Description

Optimize by trying out predefined configurations.

: The PointSearch class is similair to the GridSearch class by the property that it optimizes a model in a single pass just trying out a predefined number of parameter configurations. The main difference is that every parameter configuration has to be explicitly defined. It is not possible to define a set of values for every axis; see GridSearch for this purpose. Thus, the PointSearch class allows for more flexibility.

If no configure method is called, this class just samples random points. They are uniformly distributed in [-1,1]. parameters^2 points but minimum 20 are sampled in this case.

Definition at line 564 of file GridSearch.h.

Constructor & Destructor Documentation

◆ PointSearch()

shark::PointSearch::PointSearch ( )

inline

Constructor.

Definition at line 568 of file GridSearch.h.

References m_configured.

Member Function Documentation

◆ configure() [1/2]

void shark::PointSearch::configure ( const std::vector< RealVector > & points )

inline

Initialization of the search points.

Parameters

points array of points to evaluate

Definition at line 580 of file GridSearch.h.

References m_configured, and m_points.

Referenced by init().

◆ configure() [2/2]

void shark::PointSearch::configure	(	size_t	parameters,
		size_t	samples,
		double	min,
		double	max
	)

inline

samples random points in the range [min,max]^parameters

Definition at line 586 of file GridSearch.h.

References shark::random::globalRng, m_configured, m_points, RANGE_CHECK, and shark::random::uni().

◆ init()

void shark::PointSearch::init	(	ObjectiveFunctionType const &	objectiveFunction,
		SearchPointType const &	startingPoint
	)

inlinevirtual

If the class wasn't configured before, this method samples random uniform distributed points in [-1,1]^n.

Implements shark::AbstractSingleObjectiveOptimizer< RealVector >.

Definition at line 617 of file GridSearch.h.

References shark::AbstractOptimizer< PointType, ResultT, SolutionTypeT >::checkFeatures(), configure(), m_configured, and shark::sqr().

◆ name()

std::string shark::PointSearch::name ( ) const

inlinevirtual

From INameable: return the class name.

Reimplemented from shark::INameable.

Definition at line 573 of file GridSearch.h.

◆ read()

virtual void shark::PointSearch::read ( InArchive & archive )

inlinevirtual

Read the component from the supplied archive.

Parameters

[in,out] archive The archive to read from.

Reimplemented from shark::ISerializable.

Definition at line 600 of file GridSearch.h.

References shark::AbstractSingleObjectiveOptimizer< RealVector >::m_best, m_configured, and m_points.

◆ step()

void shark::PointSearch::step ( ObjectiveFunctionType const & objectiveFunction )

inline

Please note that for the point search optimizer it does not make sense to call step more than once, as the solution does not improve iteratively.

Definition at line 631 of file GridSearch.h.

References shark::AbstractSingleObjectiveOptimizer< RealVector >::m_best, and m_points.

◆ write()

virtual void shark::PointSearch::write ( OutArchive & archive ) const

inlinevirtual

Write the component to the supplied archive.

Parameters

[in,out] archive The archive to write to.

Reimplemented from shark::ISerializable.

Definition at line 608 of file GridSearch.h.

References shark::AbstractSingleObjectiveOptimizer< RealVector >::m_best, m_configured, and m_points.

Member Data Documentation

◆ m_configured

bool shark::PointSearch::m_configured

protected

verbosity level

Definition at line 658 of file GridSearch.h.

Referenced by configure(), configure(), init(), PointSearch(), read(), and write().

◆ m_points

std::vector<RealVector> shark::PointSearch::m_points

protected

The array holds one parameter configuration in every column.

Definition at line 655 of file GridSearch.h.

Referenced by configure(), configure(), read(), step(), and write().

The documentation for this class was generated from the following file:

include/shark/Algorithms/DirectSearch/GridSearch.h

Public Member Functions

Protected Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ PointSearch()

Member Function Documentation

◆ configure() [1/2]

◆ configure() [2/2]

◆ init()

◆ name()

◆ read()

◆ step()

◆ write()

Member Data Documentation

◆ m_configured

◆ m_points